Transmission of Policy Shocks in a Monetary Asset-Pricing Model

In a framework of a two-country monetary asset-pricing model with production the effects of stochastic and structural fiscal and monetary policy shocks are investigated. The model is kept simple enough to allow the derivation of closed form solutions of the functional equation system for the equilibrium price functions. With money yielding liquidity services in the exchange process some correlation results are derived, especially for the impact of structural and stochastic policy shocks on stock prices, exchange rates etc. Furthermore it is investigated whether shares can provide protection against inflation resulting from monetary shocks.

Using a Multi-Trait Approach to Manipulate Plant Functional Diversity in a Biodiversity-Ecosystem Function Experiment

A frequent pattern emerging from biodiversity-ecosystem function studies is that functional group richness enhances ecosystem functions such as primary productivity. However, the manipulation of functional group richness goes along with major disadvantages like the transformation of functional trait data into categories or the exclusion of functional differences between organisms in the same group. In a mesocosm study we manipulated plant functional diversity based on the multi-trait Functional Diversity (FD)-approach of Petchey and Gaston by using database data of seven functional traits and information on the origin of the species in terms of being native or exotic. Along a gradient ranging from low to high FD we planted 40 randomly selected eight-species mixtures under controlled conditions. We found a significant positive linear correlation of FD with aboveground productivity and a negative correlation with invasibility of the plant communities. Based on community-weighted mean calculations for each functional trait, we figured out that the traits N-fixation and species origin, i.e. being native or exotic, played the most important role for community productivity. Our results suggest that the identification of the impact of functional trait diversity and the relative contributions of relevant traits is essential for a mechanistic understanding of the role of biodiversity for ecosystem functions such as aboveground biomass production and resistance against invasion

Assessing language dominance with functional MRI: The role of control tasks and statistical analysis

There is a discrepancy between the brain regions revealed by functional neuroimaging techniques and those brain regions where a loss of function, either by lesion or by electrocortical stimulation, induces language disorders. To differentiate between essential and non-essential language-related processes, we investigated the effects of linguistic control tasks and different analysis methods for functional MRI data. Twelve subjects solved two linguistic generation tasks: (1) a verb generation task and (2) an antonym generation task (each with a linguistic control task on the phonological level) as well as two decision tasks of semantic congruency (each with a cognitive high-level control task). Differential contrasts and conjunction analyses were carried out on the single-subject level and an individual lateralization index (LI) was computed. On the group level we determined the percent signal change in the left inferior frontal gyrus (IFG: BA 44 and BA 45). The conjunction analysis of multiple language tasks led to significantly greater absolute LIs than the LIs based on the single task versus fixation contrasts. A further significant increase of the magnitude of the LIs could be achieved by using the phonological control conditions. Although the decision tasks appear to be more robust to changes in the statistical threshold, the combined generation tasks had an advantage over the decision tasks both for assessing language dominance and locating Broca's area. These results underline the need for conjunction analysis based on several language tasks to suppress highly task-specific processes. They also point to the need for high-level cognitive control tasks to partial out general, language supporting but not language critical processes. Higher absolute LIs, which reflect unambiguously hemispheric language dominance, can be thus obtained

Greenhouse- and Field-Measured Plant-Soil Feedbacks Are Not Correlated

Plant-soil feedbacks (PSFs) have become a commonly invoked mechanism of plant coexistence and abundance. Yet, most PSF experiments have been performed in greenhouse conditions. To test whether or not greenhouse-measured PSF values are of similar magnitude and positively correlated with field-measured PSFs, we compared PSF values from five different studies that measured PSF values in both greenhouse and field conditions. For 36 plant species, greenhouse-measured PSF values were larger than and not positively correlated with field-measured PSF values. Similarly, these 36 species produced 269 soil-specific PSF values, and for each site there was no positive correlation between these greenhouse- and field-measured PSF values. While PSFs were observed in both greenhouse and field conditions, results provided no support at the soil, site or species level that a positive correlation exists between greenhouse- and field-measured PSF. Further, greenhouse-measured PSF appear to overestimate field-measured PSF. Although from five studies, results strongly suggest that field experiments are needed to understand the role of PSFs in plant communities in natural settings

Analyzing non-equilibrium quantum states through snapshots with artificial neural networks

Current quantum simulation experiments are starting to explore non-equilibrium many-body dynamics in previously inaccessible regimes in terms of system sizes and time scales. Therefore, the question emerges which observables are best suited to study the dynamics in such quantum many-body systems. Using machine learning techniques, we investigate the dynamics and in particular the thermalization behavior of an interacting quantum system which undergoes a dynamical phase transition from an ergodic to a many-body localized phase. A neural network is trained to distinguish non-equilibrium from thermal equilibrium data, and the network performance serves as a probe for the thermalization behavior of the system. We test our methods with experimental snapshots of ultracold atoms taken with a quantum gas microscope. Our results provide a path to analyze highly-entangled large-scale quantum states for system sizes where numerical calculations of conventional observables become challenging.Comment: 4+3 pages, 3+6 figure

Signatures of bath-induced quantum avalanches in a many-body--localized system

Strongly correlated systems can exhibit surprising phenomena when brought in a state far from equilibrium. A spectacular example are quantum avalanches, that have been predicted to run through a many-body--localized system and delocalize it. Quantum avalanches occur when the system is locally coupled to a small thermal inclusion that acts as a bath. Here we realize an interface between a many-body--localized system and a thermal inclusion of variable size, and study its dynamics. We find evidence for accelerated transport into the localized region, signature of a quantum avalanche. By measuring the site-resolved entropy we monitor how the avalanche travels through the localized system and thermalizes it site by site. Furthermore, we isolate the bath-induced dynamics by evaluating multipoint correlations between the bath and the system. Our results have fundamental implications on the robustness of many-body--localized systems and their critical behavior.Comment: 5+2 pages, 4 figure

Association of analgosedation with psychiatric symptoms and health-related quality of life in ARDS survivors: post hoc analyses of the DACAPO study

Background The acute respiratory distress syndrome (ARDS) is a life-threatening condition with the risk of developing hypoxia and thus requires for invasive mechanical ventilation a long-term analgosedation. Yet, prolonged analgosedation may be a reason for declining health-related quality of life (HRQoL) and the development of psychiatric disorders. Methods We used data from the prospective observational nation‑wide ARDS study across Germany (DACAPO) to investigate the influence of sedation and analgesia on HRQoL and the risk of psychiatric symptoms in ARDS survivors 3, 6 and 12 months after their discharge from the intensive care unit (ICU). HRQoL was measured with the Physical and Mental Component Scale of the Short‑Form 12 Questionnaire (PCS‑12, MCS‑12). The prevalence of psychiatric symptoms (depression and post‑traumatic stress disorder [PTSD]) was assessed using the Patient Health Questionnaire‑9 and the Post‑Traumatic Stress Syndrome‑14. The associations of analgosedation with HRQoL and psychiatric symptoms were investigated by means of multivariable linear regression models. Results The data of 134 ARDS survivors (median age [IQR]: 55 [44–64], 67% men) did not show any significant association between analgosedation and physical or mental HRQoL up to 1 year after ICU discharge. Multivariable linear regression analysis (B [95%‑CI]) yielded a significant association between symptoms of psychiatric disorders and increased cumulative doses of ketamine up to 6 months after ICU discharge (after 3 months: depression: 0.15 [0.05, 0.25]; after 6 months: depression: 0.13 [0.03, 0.24] and PTSD: 0.42 [0.04, 0.80)]). Conclusions Up to 1 year after ICU discharge, analgosedation did not influence HRQoL of ARDS survivors. Prolonged administration of ketamine during ICU treatment, however, was positively associated with the risk of psychiatric symptoms. The administration of ketamine to ICU patients with ARDS should be with caution

Biodiversity maintains soil multifunctionality and soil organic carbon in novel urban ecosystems

1. Biodiversity in urban ecosystems has the potential to increase ecosystem functions and support a suite of services valued by society, including services provided by soils. Specifically, the sequestration of carbon in soils has often been advocated as a solution to mitigate the steady increase in CO2 concentration in the atmosphere as a key driver of climate change. However, urban ecosystems are also characterized by an often high level of ecological novelty due to profound human‐mediated changes, such as the presence of high numbers of non‐native species, impervious surfaces or other disturbances. Yet it is poorly understood whether and how biodiversity affects ecosystem functioning and services of urban soils under these novel conditions. 2. In this study, we assessed the influence of above‐ and below‐ground diversity, as well as urbanization and plant invasions, on multifunctionality and organic carbon stocks of soils in non‐manipulated grasslands along an urbanization gradient in Berlin, Germany. We focused on plant diversity (measured as species richness and functional trait diversity) and, in addition, on soil organism diversity as a potential mediator for the relationship of plant species diversity and ecosystem functioning. 3. Our results showed positive effects of plant diversity on soil multifunctionality and soil organic carbon stocks along the entire gradient. Structural equation models revealed that plant diversity enhanced soil multifunctionality and soil organic carbon by increasing the diversity of below‐ground organisms. These positive effects of plant diversity on soil multifunctionality and soil fauna were not restricted to native plant species only, but were also exerted by non‐native species, although to a lesser degree. 4. Synthesis. We conclude that enhancing diversity in plants and soil fauna of urban grasslands can increase the multifunctionality of urban soils and also add to their often underestimated but very valuable role in mitigating effects of climate change

protocol for a prospective, observational, multi-centre patient cohort study (DACAPO)

Background Health-related quality of life (HRQoL) and return to work are important outcomes in critical care medicine, reaching beyond mortality. Little is known on factors predictive of HRQoL and return to work in critical illness, including the acute respiratory distress syndrome (ARDS), and no evidence exists on the role of quality of care (QoC) for outcomes in survivors of ARDS. It is the aim of the DACAPO study (“Surviving ARDS: the influence of QoC and individual patient characteristics on quality of life”) to investigate the role of QoC and individual patient characteristics on quality of life and return to work. Methods/Design A prospective, observational, multi-centre patient cohort study will be performed in Germany, using hospitals from the “ARDS Network Germany” as the main recruiting centres. It is envisaged to recruit 2400 patients into the DACAPO study and to analyse a study population of 1500 survivors. They will be followed up until 12 months after discharge from hospital. QoC will be assessed as process quality, structural quality and volume at the institutional level. The main outcomes (HRQoL and return to work) will be assessed by self-report questionnaires. Further data collection includes general medical and ARDS-related characteristics of patients as well as sociodemographic and psycho-social parameters. Multilevel hierarchical modelling will be performed to analyse the effects of QoC and individual patient characteristics on outcomes, taking the cluster structure of the data into account. Discussion By obtaining comprehensive data at patient and hospital level using a prospective multi-centre design, the DACAPO-study is the first study investigating the influence of QoC on individual outcomes of ARDS survivors